The AI Engineering Bootcamp
Dr. Greg Loughnane, Ph.D.
CEO @ AI Makerspace
Chris "The Wiz 🪄" Alexiuk
AI & OSS @ NVIDIA
This course is popular
3 people enrolled last week.
The bootcamp for professionals, NOT beginners.
This course started in January 2024 as the next evolution of LLM Ops, Cohort 4.
Two years later, Cohort 9 (v0.9) marked the end of the next chapter.
Check out the curriculum changelog from Cohorts 1-9 and track what our certified grads are doing today. Ask them about their journeys!
Free versions of our content are available on YouTube and GitHub.
We continue on our 🚩 mission to create the industry-standard certification for people who want to become AI Engineers.
In 2026, our journey into the enterprise has begun; we're working with companies to learn what matters most for production AI Engineers & their teams.
When aimakerspace.io launches our next course, we'll bring back the lessons we learn along the way.
-- Course Info --
This course was designed for backend engineers who code every day and have decided it's time to go all in on building production AI applications.
In just 10 weeks of building 🏗️, shipping 🚢, and sharing 🚀, you supercharge your abilities.
TL;DR v0.9: Agentic AI
🕴️Agentic RAG (2 wks)
🧰 Complex Agents (2 wks)
📊 Evals (1.5 wks)
🚀 Certification Challenge (1.5 wks)
🚢 Production Deployments (2 wks)
🤩 Demo Day (1 wk)
Learn more here: detailed curriculum.
What you’ll learn
To build AI agents that create real value for people and companies. Without the fluff.
What are the similarities and differences between RAG, Agents, Agentic RAG, Deep Agents, and Multi-Agent Applications?
What is agent memory, short-term and long-term, and how does its implementation overlap with other key prototyping design patterns.
How do we evaluate agents, exactly, from goals to tools to traces?
Prompt engineering, RAG, agents, and fine-tuning are fundamental design patterns we need to leverage to manage context - how do we use them?
How does context engineering look in agentic systems that include many conversation turns, multiple agents, or many user sessions?
How do we make tradeoff decisions on what to put in the context window, whether enhancing or pruning context?
How can we learn to use any tools? By going deep on a single set of opinionated best-practice tools during learning.
How can we avoid vendor lock-in? Stay open-source-first during tool selection for maximum flexibility.
Do I need to learn cloud service providers like AWS? No. You must learn to prototype and deploy to production; these are not the same.
Builders can build, but when they start sharing, they unlock the next level. THIS is what our community tells us makes us different.
Through sharing what you learn, build, ship, and share each week, you become the de facto expert in your personal network.
Learn to build industry-relevant $5-15k POCs in 10-40 hours (based on our Certified AI Engineer data).
How can you learn to code when the agent can do it better than you? Answer: Don't let it code anything you don't understand.
How can I become someone who gets a job or is recommended for hiring in 2026? Answer: leverage coding agents EXACTLY the right amount.
What's the point of learning to use Cursor when my company has Copilot? Answer: Feature parity is coming - now is the time to get ahead.
Who this course is for
Software engineers and developers who want to build, deploy, operate, and improve LLM apps in production environments.
The very best ML engineers who are pseudo-software engineers and have not lived in notebooks, and who want to build, deploy, ... etc.
What's included
Live sessions
Learn directly from Dr. Greg Loughnane, Ph.D. & Chris "The Wiz 🪄" Alexiuk in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund through the second week of the course.
Course syllabus
23 live sessions • 60 lessons • 19 projects
Week 1
Jan
14
Session 1: ✨ Vibe Check
Wed 1/1412:00 AM—2:00 AM (UTC)Jan
16
Session 2: 🗃️ Dense Vector Retrieval
Fri 1/1612:00 AM—2:00 AM (UTC)
✨ Vibe Check
🗃️ Dense Vector Retrieval
🧑🏫 Weekly Office Hours
🌍🌏 EMEA Weekly Meetup
🌐 FREE Community Sessions!
Week 2
Jan
21
Session 3: 🔁 The Agent Loop
Wed 1/2112:00 AM—2:00 AM (UTC)Jan
23
Session 4: 🕴️ Agentic RAG
Fri 1/2312:00 AM—2:00 AM (UTC)
🔁 The Agent Loop
🕴️ Agentic RAG
Free resource
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Context Engineering for Agents & Multi-Agent Systems
Context Engineering is the new...
Not just prompt engineering, but also RAG! Learn why this fundamentally makes intuitive sense for Generative AI
How agents with tools help us to enhance context
Enhancing search and retrieval is the primary job of agents with access to tools (and MCP servers!) today
How multi-agent systems enhance context
How tools like Deep Research offer insights into using parallelization to further scale context optimization
Schedule
Live sessions
4 hrs / week
We hold class every Tuesday and Thursday at 7-9 PM ET! It's important to show up live to these sessions, as you'll always get your questions answered and get ~35-50 minutes of live breakout room time to do your homework!
Wed, Jan 14
12:00 AM—2:00 AM (UTC)
Fri, Jan 16
12:00 AM—2:00 AM (UTC)
Wed, Jan 21
12:00 AM—2:00 AM (UTC)
Projects
5-10 hrs / week
Weekly projects can be time-consuming, especially early on in the cohort, and even with the time spent live in class working on them. On average, you should budget about this much time. During Week 6, our Certification Challenge typically requires students 20-30 hours. During Weeks 9-10, Demo Day can also be quite time-consuming.
Instructor and Peer Supporter Office Hours
1-12 hrs / week
Each week, we will have our staff of 10 peer supporters (all Certified AI Engineers from the Bootcamp) and both instructors each hold an office hour. You can attend none or all of them, as you wish!
Testimonials
I want to thank Dr. Greg, The Wiz, and the entire AIM team. None of my projects like PromptLab (https://promptlab.so) and OpenEvals (https://open-evals.com) would have been possible without the course and the Build, Ship, and Share mentality. Simply sharing what I’ve built on X helped the framework gain visibility from thought leaders in the Vercel AI SDK and Typescript developer communities, and opened doors for new opportunities. Taking this class has truly changed my life.
Can Temizyurek
20 year old Context Engineer - Dream is to work at Vercel - Creator of open-evals.com - vibecoders.com - promptlab.soI joined AI Makerspace while looking to start my company, Publicus, and it’s also where I met my co-founder Joe. What amazed me was how inclusive the community is technical folks, researchers, and even non-developers and yet everyone still built, shipped, and shared real projects. The program completely reshaped how I use open-source tools and ship to production fast. I still rely on the teachings from Dr. Greg and Wiz today. RAGAS and EvolInstruct were game-changing takeaways that I now use to reduce hallucinations and build more reliable AI systems. It’s genuinely the best community for people who want to build real things in the real world
Akash Shetty
CTO @ PublicusThe AI Engineering Bootcamp gave me practical skills I use every day building Publicus. Every week, we implemented real AI packages and frameworks that I now use in production. Beyond the technical skills, the bootcamp helped me understand how to actually build agentic products—not just talk about them. Most importantly, I met my co-founder Akash there, and the network I built continues to be incredibly valuable. If you want to go from understanding AI concepts to shipping AI products, this is it.
🌐 https://publicus.ai/
Joe Noss
Co-Founder & CEO @ PublicusThe Aithon journey started out of AIE4 cohort in the AI Makerspace bootcamp. A year later, the project idea has morphed into an AI-native GTM platform for regulated financial services. We are helping large Fintechs grow and expand their presence in enterprise financial services accounts. We combine external public and proprietary signals with customer’s first party data to spot whitespace and drive expansion across financial services enterprise accounts.
Nitin Gupta
Co-Founder & CEO @ AithonI want to thank Dr. Greg, The Wiz, and the entire AI Makerspace community for creating an environment where theory becomes real traction. The program gave me the clarity and technical rigor to architect Elysia—Informa’s enterprise GenAI platform now used by 20,000+ colleagues across the globe. The “build, ship, share” mindset pushed me beyond demos into production-grade retrieval pipelines, multi-agent orchestration, and scalable AI foundations that drive measurable impact. This community has been transformative for my work, and I’m grateful for the support and inspiration throughout the journey.
Arthi Kasturirangan
Head of AI Engineering @ Informa
Garret G.
Founder @ DeepWriter
Build 🏗️ Ship 🚢 Share 🚀 Is the Way
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Read more at https://thedataguy.pro/blog/2025/05/build-ship-share/
Cohort 8 Transformations, by Self-Assessment
We ask students to self-assess along 9 dimensions when they start and finish the bootcamp!
Certification Challenge Results, Cohort 8
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Learn to build, ship, and share production-grade prototypes worth real cash with real customers.
The State of AI Engineering 2025
We break it down heading into 2026: https://bit.ly/state-of-aie-25 (live streamed on Nov 12, 2025)
LangChain v1.0
Get head of the course: https://bit.ly/langchain-v1 (live streamed on Nov 19, 2025)
LLM Engineering, Cohort 3 [2024] (Open-Sourced)
https://github.com/AI-Maker-Space/LLM-Engineering-Foundations-to-SLMs-Open-Source
LLM Ops, Cohort 1 [2023] (Open-Sourced in 2023)
https://github.com/AI-Maker-Space/LLM-Ops-Cohort-1